<![CDATA[Electronic Medical Records (EMR) play a crucial role in supporting healthcare services and clinical decision-making, yet family history recording remains unstructured and underutilized in healthcare practice. This situation necessitates the identification of the most essential family history data elements to ensure more focused, consistent, and applicable recording. This study aims to identify a minimum family history dataset in EMR as a basis for early detection of genetic diseases. The research method used was a two-round Delphi method involving a 15-member expert panel consisting of clinicians, senior medical records personnel, and medical records experts. The results showed that in the first round of the Delphi, of the 15 initial family history elements evaluated, 12 elements met the context, while 3 elements were excluded because they were deemed inadequate for consistent recording. Two additional elements emerged based on input from the panel of experts. In the second Delphi round, all 14 evaluated elements reached consensus with a median value ≥ 4 and an IQR ≤ 1. These elements include family structure, family disease history, and genetic patterns and risks that are considered clinically important and relevant to daily healthcare practice. This study resulted in 14 minimum elements of a family history dataset that can be used as a conceptual basis for the development or integration of more structured family history recording into an EMR system to support early detection of genetic diseases.]]>
